Evidence map›Paper›PMID 37224807›Full record

ArticleAmerican journal of human genetics2023

Impact of cross-ancestry genetic architecture on GWASs in admixed populations.

Rachel Mester, Kangcheng Hou, Yi Ding, Gillian Meeks, Kathryn S Burch, Arjun Bhattacharya, Brenna M Henn, Bogdan Pasaniuc

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in American journal of human genetics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed
11.0field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

34 citing papers in PubMed, 35 citations in OpenAlex.

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  14. Revisiting the Trans-Ancestry Genetic Correlation of Refractive Error.Investigative ophthalmology & visual science · 2025
    Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 2 institutions in 1 country.

Rachel MesterDepartment of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA. Electronic address: rmester@ucla.edu.
Kangcheng HouBioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA 90095, USA.
Yi DingBioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA 90095, USA.
Gillian MeeksIntegrative Genetics and Genomics Graduate Group, University of California, Davis, Davis, CA 95616, USA.
Kathryn S BurchBioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA 90095, USA.
Arjun BhattacharyaDepartment of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA.
Brenna M HennDepartment of Anthropology, Center for Population Biology and the Genome Center, University of California, Davis, Davis, CA 95616, USA.
Bogdan PasaniucDepartment of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Institute of Precision Health, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA. Electronic address: pasaniuc@ucla.edu.
University of California, Los Angeles · USUniversity of California, Davis · US

Funding

Training Grant in Genomic Analysis and InterpretationT32HG002536 · NHGRI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Valerie A Arboleda, Harold Pimentel · 2002 to 2026
$8.6M
Methods for Genome-wide Association Studies in Admixed PopulationsR01HG006399 · NHGRI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI PRICE, ALKES L · 2011 to 2024
$6.3M
PRS Center for Admixed Populations (CAPE)U01HG011715 · NHGRI · UNIVERSITY OF PENNSYLVANIA · PI Eimear Elizabeth Kenny, Leslie A Lange · 2021 to 2026
$5.2M
Supplement: Improving Inference of Genetic Architecture and Selection with African GenomesR35GM133531 · NIGMS · UNIVERSITY OF CALIFORNIA AT DAVIS · PI HENN, BRENNA M · 2019 to 2023
$2.3M
Integrative approaches for mapping the genetic risk of complex traitsR01HG009120 · NHGRI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI PASANIUC, BOGDAN · 2017 to 2021
$2.3M
NHGRI NIH HHS R01 HG006399NHGRI NIH HHS R01 HG009120NHGRI NIH HHS T32 HG002536NHGRI NIH HHS U01 HG011715NIGMS NIH HHS R35 GM133531
6 · The paper itself

Abstract

Genome-wide association studies (GWASs) have identified thousands of variants for disease risk. These studies have predominantly been conducted in individuals of European ancestries, which raises questions about their transferability to individuals of other ancestries. Of particular interest are admixed populations, usually defined as populations with recent ancestry from two or more continental sources. Admixed genomes contain segments of distinct ancestries that vary in composition across individuals in the population, allowing for the same allele to induce risk for disease on different ancestral backgrounds. This mosaicism raises unique challenges for GWASs in admixed populations, such as the need to correctly adjust for population stratification. In this work we quantify the impact of differences in estimated allelic effect sizes for risk variants between ancestry backgrounds on association statistics. Specifically, while the possibility of estimated allelic effect-size heterogeneity by ancestry (HetLanc) can be modeled when performing a GWAS in admixed populations, the extent of HetLanc needed to overcome the penalty from an additional degree of freedom in the association statistic has not been thoroughly quantified. Using extensive simulations of admixed genotypes and phenotypes, we find that controlling for and conditioning effect sizes on local ancestry can reduce statistical power by up to 72%. This finding is especially pronounced in the presence of allele frequency differentiation. We replicate simulation results using 4,327 African-European admixed genomes from the UK Biobank for 12 traits to find that for most significant SNPs, HetLanc is not large enough for GWASs to benefit from modeling heterogeneity in this way.

Indexed as

Genetics, PopulationGenome-Wide Association StudyGene FrequencyGenotypeHumansPhenotypePolymorphism, Single Nucleotideadmixturecomplex traiteffect sizesgenetic ancestrygenetic correlationGWASheterogeneitylocal ancestrysimulationTractor

Identifiers

PMID37224807
PMCPMC10257009
OpenAlexW4377694925

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.